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NASA NTRS2016

Why Deep Space Habitats Should Be Different from the International Space Station

It is tempting to view the International Space Station (ISS) as a model for deep space habitats. This is not a good idea for many reasons. The ISS does not have a habitation module; instead the individual crew quarters are dispersed across several modules, the galley is in the US Laboratory and the waste hygiene compartment is in a Node. This distributed arrangement may be inconvenient but more important differences distinguish a deep space habitat from the ISS. First, the Space Shuttle launch system that shaped, sized, and delivered most ISS elements has been retired. Its replacement, the Space Launch System (SLS), is specifically designed for human exploration beyond low-Earth orbit and is capable of transporting more efficient, large diameter, heavy-lift payloads. Next, because of the Earth's protective geomagnetic field, ISS crews are naturally shielded from lethal radiation. Deep space habitat designs must include either a storm shelter or strategically positioned equipment and stowage for radiation protection. Another important difference is the increased transit time with no opportunity for an ISS-type emergency return. It takes 7 to 10 days to go between Earth and cis-lunar locations and 1000 days for the Mars habitat transit. This long commute calls for greater crew autonomy with habitats designed for the crew to fix their own problems. The ISS rack-enclosed, densely packaged subsystems are a product of the Shuttle era and not maintenance friendly. A solution better suited for deep space habitats spreads systems out allowing direct access to single-layer packaging and providing crew access to each component without having to remove another. Operational readiness is another important discriminator. The ISS required over 100 flights to build, resupply, and transport the crew, whereas SLS offers the capability to launch a fully provisioned habitat that is operational without additional outfitting or resupply flights.

Griffin, Brand↗
NASA NTRS2017

The First Deep Space Cubesat Broadband IR Spectrometer, Lunarcubes, and the Search for Lunar Volatiles

BIRCHES is the compact broadband IR spectrometer of the Lunar Ice Cube mission. Lunar Ice Cube is one of 13 6U cubesats that will be deployed by EM1 in cislunar space, qualifying as lunarcubes. The LunarCube paradigm is a proposed approach for extending the affordable CubeSat standard to support access to deep space via cis-lunar/lunar missions. Because the lunar environment contains analogs of most solar system environments, the Moon is an ideal target for both testing critical deep space capabilities and understanding solar system formation and processes. Effectively, as developments are occurring in parallel, 13 prototype deep space cubesats are being flown for EM1. One useful outcome of this 'experiment' will be to determine to what extent it is possible to develop a lunarcube 'bus' with standardized interfaces to all subsystems using reasonable protocols for a variety of payloads. The lunar ice cube mission was developed as the test case in a GSFC R&D study to determine whether the cubesat paradigm could be applied to deep space, science requirements driven missions, and BIRCHES was its payload. JPL's Lunar Flashlight, and Arizona State University's LunaH-Map, both also EM1 lunar orbiters, will also be deployed from EM1 and provide complimentary observations to be used in understanding volatile dynamics in the same time frame.

Cubesat↗
NASA NTRS2015

An Innovative Very Low Thermal Power Waste Heat Recovery System for Thermal Control of Deep Space Missions: A Thermal Flask in Space

Future missions to deep space, such as those to the outer planets (Jupiter, Saturn, etc.), which would rely on solar photovoltaic power, would need extremely large solar arrays to produce sufficient power for their operations because solar intensity is so low at those locations. Hence any additional power that would be needed for thermal control is extremely limited. Previous deep space missions like Juno (to Jupiter) required almost 200 W of electrical power for thermal control. This is prohibitively large for many future mission concepts, and leads to them needing very large solar arrays. For Saturn, where the solar flux is 1/4th the flux at Jupiter, this would entail an extremely large increase in the solar array size to accommodate the need for thermal survival power, which would be prohibitively large in size and mass, and very expensive. Hence there is a need to come up with a thermal architecture and design options that would not need such prohibitively large thermal power levels. One solution relies on harvesting the pre-existing waste heat from all the heat dissipation that would be present from operation of electronics, instruments, etc. for their own functionality. For example, for a generic Saturn mission, the various electronics would already dissipate about 200 Watts of heat that is simply "thrown away" to space from the spacecraft surfaces. The amount of thermal power that would be required for the safe thermal control of components within the spacecraft in deep space would be roughly of this magnitude for this class of spacecraft. So it makes good sense to try to harvest the waste heat and employ it to maintain the temperatures of all the components within their allowable limits. In particular, propulsion systems typically need to be kept above their freezing limits, around room temperature (15 C). Electronics needs to be kept typically above -40 C and batteries above -20 C. The next question becomes how to harvest this waste heat and direct it to the components that would need it for their survival. The proposed system utilizes a mechanically pumped, single phase fluid loop to pick up the waste heat from components attached to this loop's tubing and then directed to a thermal flask that has tubing attached to it. The thermal flask is cylindrically shaped and contains essentially all systems and components in the spacecraft within it, with the exception of the solar array, antennae, thrusters and various apertures of instruments, etc. to allow them an unobstructed view of space. Waste heat from the heat-dissipating components warms up the fluid and is carried to the flask surface and deposited on it via the fluid loop's flow. The entire flask is covered with Multi-Layered Insulation (MLI) to minimize the heat loss from the flask and allow it to remain warm. Hence the flask essentially creates a thermal environment within which the spacecraft components reside. The temperature of the components within the flask is then essentially the same as the temperature of the flask. This approach could be a very enabling feature for deep space missions. This paper describes the approach utilized for this thermal architecture, along with its mechanical and implementation aspects. Additionally it will compare and contrast this approach with the more conventional solutions utilized earlier.

Bhandari, Pradeep↗
NASA NTRS2016

The Auto-Gopher: A Wireline Rotary-Percussive Deep Sampler

Accessing regions on planetary bodies that potentially preserved biosignatures or are presently habitable is vital to meeting NASA solar system "Search for Life" exploration objectives. To address these objectives, a wireline deep rotary-percussive corer called Auto-Gopher was developed. The percussive action provides effective material fracturing and the rotation provides effective cuttings removal. To increase the drill's penetration rate, the percussive and rotary motions are operated simultaneously. Initially, the corer was designed as a percussive mechanism for sampling ice and was demonstrated in 2005 in Antarctica reaching about 2 m deep. The lessons learned suggested the need to use a combination of rotation and hammering to maximize the penetration rate. This lesson was implemented into the Auto-Gopher-I deep drill which was demonstrated to reach 3-meter deep in gypsum. The average drilling power that was used has been in the range of 100-150 Watt, while the penetration rate was approximately 2.4 m/hr. Recently, a task has started with the goal to develop Auto-Gopher-II that is equipped to execute all the necessary functions in a single drilling unit. These functions also include core breaking, retention and ejection in addition drilling. In this manuscript, the Auto-Gopher-II, its predecessors and their capability are described and discussed.

drilling↗
NASA NTRS2017

Building Better Biosensors for Exploration into Deep-Space, Using Humanized Yeast

1.BioSentinel is 1 of 13 secondary payloads hitching a ride beyond Low Earth Orbit on Exploration Mission 1 (EM-1), set to launch from NASAs Space Launch System in 2019. EM-1 is our first opportunity to investigate the effects of the deep space environment on a eukaryotic biological system, the budding yeast S. cerevisiae. Though separated by a billion years of evolution we share hundreds of genes important for basic cell function, including responses to DNA damage. Thus, yeast is an ideal biosensor for detecting typesextent of damage induced by deep-space radiation.We will fly desiccated cells, then rehydrate to wake them up when the automated payload is ready to initiate the experiment. Rehydration solution contains SC (Synthetic Complete) media and alamarBlue, an indicator for changes in growth and metabolism. Telemetry of LED readings will then allow us to detect how cells respond throughout the mission. The desiccation-rehydration process can be extremely damaging to cells, and can severely diminish our ability to accurately measure and model cellular responses to deep-space radiation. The aim of this study is to develop a better biosensor: yeast strains that are more resistant to desiccation stress. We will over-express known cellular protectants, including hydrophilin Sip18, the protein disaggregase Hsp104, and thioredoxin Trx2, a responder to oxidative stress, then measure cell viability after desiccation to determine which factors improve stress tolerance. Over-expression of SIP18 in wine yeast starter cultures was previously reported to increase viability following desiccation stress by up to 70. Thus, we expect similar improvements in our space-yeast strains. By designing better yeast biosensors we can better prepare for and mitigate the potential dangers of deep-space radiation for future missions.This work is funded by NASAs AES program.

biosensor↗
NASA NTRS2017

NASA's Space Launch System: A Transformative Capability for Deep Space Missions

Already making substantial progress toward its first launches, NASA’s Space Launch System (SLS) exploration-class launch vehicle presents game-changing new opportunities in spaceflight, enabling human exploration of deep space, as well as a variety of missions and mission profiles that are currently impossible. Today, the initial configuration of SLS, able to deliver more than 70 metric tons of payload to low Earth orbit (LEO), is well into final production and testing ahead of its planned first flight, which will send NASA’s new Orion crew vehicle around the moon and will deploy 13 CubeSats, representing multiple disciplines, into deep space. At the same time, production work is already underway toward the more-capable Block 1B configuration, planned to debut on the second flight of SLS, and capable of lofting 105 tons to LEO or of co-manifesting large exploration systems with Orion on launches to the lunar vicinity. Progress being made on the vehicle for that second flight includes initial welding of its core stage and testing of one of its engines, as well as development of new elements such as the powerful Exploration Upper Stage and the Universal Stage Adapter “payload bay.” Ultimately, SLS will evolve to a configuration capable of delivering more than 130 tons to LEO to support humans missions to Mars. In order to enable human deep-space exploration, SLS provides unrivaled mass, volume, and departure energy for payloads, offering numerous benefits for a variety of other missions. For robotic science probes to the outer solar system, for example, SLS can cut transit times to less than half that of currently available vehicles or substantially increased spacecraft mass. In the field of astrophysics, SLS’ high payload volume, in the form of payload fairings with a diameter of up to 10 meters, creates the opportunity for launch of large-aperture telescopes providing an unprecedented look at our universe. This presentation will give an overview of SLS’ capabilities and its current status, and discuss the vehicle’s potential for human exploration of deep space and other game-changing utilization opportunities.

Creech, Stephen D.↗
NASA NTRS2018

NASA's Space Launch System and Deep Space Opportunities for Smallsats

Overview of the agency’s plans for deep space exploration: NASA has a phased approach to successful human exploration of deep space; We began LEO (Low Earth Orbit), where we’ve lived aboard the ISS continuously for more than 17 years; What have we learned in those years that will help us put boots on the moon with eyes toward Mars? And also help us on Earth? - Advances in materials research - 3D printing in space - Engineered life support systems for sustained stays in space - Better understanding of the effects of microgravity on the human body - We deploy CubeSats from the ISS (International Space Station) - We’ve cooperate with international partners - We’ve opened transportation to LEO to commercial vehicles; Allowing commercial companies to take over LEO frees NASA to explore deep space - next step is back to the Moon; NASA will establish a lunar Gateway near the moon (near rectilinear halo orbit);The Gateway will be crew tended (30-90 day missions); Gateway will communicate with Earth and lunar surface; Will open new opportunities for robotic exploration of the moon, especially far side of the moon and poles; Prospecting for volatiles will be high on the list of priorities; SLS (Space Launch System)/Orion will participate in gateway assembly and operation; Will serve as a testbed for new technologies and inform future Mars missions; After learning how to live and work in deep space like we did in LEO, NASA will move on Mars missions; SLS’s capability to accommodate primary, co-manifested and secondary payloads (when available) is a key component in making this vision a reality.

Bookout, Paul S.↗
NASA NTRS2016

Deep Space NanoSats - Positioned for Exponential Growth

We are poised at the beginning of a new era in solar system exploration, in which cubesats and nanosats can potentially play a big role. In 2012 a small group of like-minded enthusiasts at JPL predicted exponential growth in deep space cubesats with at least 10 exploring our solar system by 2020, and a 100 by 2030. Since then, JPL has built and flight-qualified the two INSPIRE spacecraft as pathfinders for future deep space cubesat missions, and the two MARCO spacecraft were assembled and tested in time to make the initial Insight launch opportunity in 2016 – now under consideration for the next available window. We have ongoing studies for lunar exploration and asteroid rendezvous missions, a Venus atmosphere sampler, and other concepts have been proposed to NASA. The Europa mission has 10 academic institutes under contract to study cubesats that would ride along with the main spacecraft to enable it to get closer to the surface of Jupiter’s most intriguing moon. Last year, ESA announced that its AIM asteroid probe will carry a small number of cubesats, when it launches in 2020. In the commercial world, Deep Space Industries are planning to host multiple cubesats in a mission to a Near Earth Asteroid. The prospects for near-term growth look reasonably healthy. This paper will provide an overview of deep space and LEO cubesat developments at JPL, and discuss the foundation they will provide for the growing community of interplanetary cubesat pioneers over the coming decade and a half.

Freeman, Anthony↗
NASA NTRS2016

Comparison of Atmospheric Delay Statistics from Deep Space Network Arrays and Nearby Test Interferometers

Several techniques have been explored and demonstrated that allow for greater data return on space-to-ground links. Among these techniques, arraying several smaller diameter dish antennas together is one method used in several arenas. These arrays can achieve larger effective area and gain than are available from a single larger antenna. This technique is routinely used by the NASA Deep Space Network (DSN) at 8.4 GHz where the incoming signals are much weaker than those experienced by the near-Earth satellite community. When considering arraying at much higher frequencies such as 32 GHz deep-space Ka-band, the phase alignment of the individual antenna signals is significantly disrupted by atmospheric turbulence. Since 2012, several downlink array demonstrations have been conducted using 32 GHz carrier signals emitted by the deep space probes Cassini and Kepler. Site test interferometers (STIs) that receive signals from geostationary satellites have been deployed at all three DSN tracking complexes for long-term monitoring of atmospheric delay fluctuations. In a previous DSN array demonstration study involving the Cassini spacecraft, it was shown that statistics of the adjusted STI phase fluctuations matched the statistics of concurrent array demonstration phase fluctuations. These adjustments accounted for differences in antenna separation, elevation angle and spacecraft frequencies. The STI antenna separations were about 200 m and the DSN antenna separations were about 300 m. These adjustments made use of the thick-layer turbulence model that was applicable to the Goldstone desert climate during the summer months for which the data were acquired. In this paper, we report on the results of additional array demonstrations involving the Kepler spacecraft and compare the adjusted STI phase fluctuations with those seen by a nearby two-element array of 34 m diameter antennas tracking Kepler’s 32 GHz signal at the Goldstone, California and Madrid, Spain DSN sites. We also discuss results from a demonstration using an array over a longer 12.5 km baseline. The Cassini and Kepler array demonstrations were found to validate the long term statistics acquired from several years of STI data as well as the models used to adjust the statistics for the conditions of an array. These statistics represent reliable estimates of the phase fluctuations that would be seen by an array tracking a deep space signal after applying appropriate adjustments for a given array configuration, elevation angle profile and observing frequency.

Morabito, David D.↗
NASA NTRS2018

Auto-Gopher-2 – An Autonomous Wireline Rotary Piezo-Percussive Deep Drilling Mechanism

Drilling deep into the subsurface of planetary bodies in the Solar System for samples acquisition enables critical capabilities for future NASA exploration missions in its quest to understand the origins of the Solar System and potentially the search for life. Such planetary bodies as Mars and Europa are key targets for potential missions that would require reaching great depths. Performing drilling while using minimal mass/volume systems and with low energy consumption are the main requirements that are imposed on such technologies. A wireline deep drill, called Auto-Gopher-2, is currently being developed as a joint effort between JPL and Honeybee Robotics Ltd. The Auto-Gopher II is a wireline rotary piezo-percussive deep drilling mechanism that combines formation breaking by rotating and piezoelectric actuator hammering and cuttings removal by rotating a fluted bit. The hammering mechanism is based on the Ultrasonic/Sonic Drill/Corer (USDC) mechanism that has been developed as an adaptable tool for many drilling and coring applications. The USDC uses an intermediate ball-shape free-mass to transform high frequency vibrations of a piezoelectric transducer horn tip into sonic hammering of the drill bit. The lessons learned from the previous studies are being implemented into the development of the Auto-Gopher-II, an autonomous deep wireline drill with integrated cuttings and sample management and drive electronics. Subsystems of the wireline drill are being developed in parallel at JPL and Honeybee Robotics, Ltd. Issues related to the bit and its ability to retain the cuttings for caching and removal are currently being addressed. This paper presents the development efforts of the piezoelectric actuator, cuttings removal and retention flutes and drive electronics.

Bar-Cohen, Yoseph↗
NASA NTRS2019

Deep Learning Method for Detecting Precursors to Adverse Events

With the recent advancements in Deep Learning methods, the ability to model large complex heterogeneous data sets are fundamentally changing industry and research. Coupled with hardware improvements, and ease of implementation, a wide variety of deep neural network architectures can quickly be developed to solve a sweeping range of problems such as: object detection in images, automatic healthcare diagnosis using heterogenous data sources, real time language translating and sentence prediction, upscaling low resolution images, and forecasting of multivariate timeseries. Generally, many of these architectures outperform classical machine learning approaches in their respective tasks, however, this typically comes at a cost of interpretability. These black box algorithms generally suffer from lack of transparency in both model complexity as well as the rationale behind the prediction. This lack of comprehension, is driving an emerging area of interest in “Explainable AI”. An algorithm called: “Deep Temporal Multiple Instance Learning”1 was a recently developed to identify precursors to adverse events and has been applied in the aviation domain. The deep learning architecture is designed to capture the evolution of the probability of the outcome over the time preceding the adverse event using a multiple instance learning approach as illustrated in Figure 1. Precursors are defined when the probability of the event has exceeded a threshold at some point in the timeseries, at which point, a sensitivity analysis is performed to determine contributing factors. The contributing factors are used to explain and define the precursor during the periods where the probability score is high. The identified contributing factors are then presented to subject matter experts to provide objective insights into the leading factors associated with the particular adverse event. The algorithm has been tested on flight data from a commercial airline and has the ability to discover precursors to known adverse events that take the form of safety critical operations, such as unstable approach events on final approach. Apart from detecting precursors to adverse events, the converse can also be leveraged to discover corrective actions. These positive actions manifest themselves as periods in the timeseries when the precursor score has been lowered from an elevated state; meaning that if the system had been left uncorrected, it would have eventually reached the adverse event state. Characterizing these state changes can help identify successful interventions that may not have been known before. Policy makers and procedure designers can use this additional knowledge to craft more safety and efficient resilient procedures for future operations and therefore improve the overall performance of the National Airspace.

Matthews, Bryan L.↗
NASA NTRS2019

NASA's Space Launch System: Deep Space Access for CubeSats

NASA is embarking on a new generation of missions to the Moon, known as the Artemis program. The Agency’s new super heavy-lift launch vehicle, the Space Launch System (SLS), is a critical enabling capability for these efforts, which will serve as a proving ground for future crewed expeditions to Mars. SLS is designed to return astronauts to the Moon in the Orion spacecraft and to launch more mass and provide more volume for critical payloads than commercially available vehicles, giving NASA a unique asset for deep space exploration. When performance margin and volume is available, as it is on the first flight, Artemis I (previously Exploration Mission-1), SLS can offer CubeSats access to deep space, beyond Earth’s orbit. The Artemis I flight has 13 6U (14 kg) CubeSats manifested, and the Program is currently accepting proposals for 6U and 12U payloads for the Artemis II flight through the agency’s CubeSat Launch Initiative (CSLI) program. Proposals from U.S.-based payload developers to fly on Artemis II will be accepted through CSLI until November 4, 2019. When ridesharing on SLS deep space missions, CubeSats must demonstrate they will not interfere with primary mission objectives. The 13 Artemis I CubeSats that hail from industry, academia, NASA and its international partners represent an array of exciting deep space science investigations and technology demonstrations that may help inform future Artemis missions. The initial SLS Block 1 vehicle for the Artemis I flight is fully manufactured; several elements are complete and have been delivered to the Exploration Ground Systems (EGS) Program at Kennedy Space Center (KSC), which has responsibility for integrating and launching the SLS and Orion stack. Completed elements of the Artemis I vehicle include the Orion Stage Adapter (OSA), which houses the 13 Artemis I CubeSats. With the Artemis I flight hardware and software nearing completion, work is in progress for the second Block 1 launcher, designated for the crewed Artemis II flight. Hardware is being manufactured for every element of the Artemis II vehicle. In this paper, the author will review the status of the Artemis I vehicle and the payloads manifested for the initial flight. Information on the Secondary Payload Deployment System (SPDS) that the SLS Program provides to payload developers will also be included.

Creech, Stephen D.↗
NASA NTRS2020

Improving Trust in Deep Neural Networks with Nearest Neighbors

Deep neural networks are used increasingly for perception and decision-making in UAVs. For example, they can be used to recognize objects from images and decide what actions the vehicle should take. While deep neural networks can perform very well at complex tasks, their decisions may be unintuitive to a human operator. When a human disagrees with a neural network prediction, due to the black box nature of deep neural networks, it can be unclear whether the system knows something the human does not or whether the system is malfunctioning. This uncertainty is problematic when it comes to ensuring safety. As a result, it is important to develop technologies for explaining neural network decisions for trust and safety. This paper explores a modification to the deep neural network classification layer to produce both a predicted label and an explanation to support its prediction. Specifically, at test time, we replace the final output layer of the neural network classifier by a k-nearest neighbor classifier. The nearest neighbor classifier produces 1) a predicted label through voting and 2) the nearest neighbors involved in the prediction, which represent the most similar examples from the training dataset. Because prediction and explanation are derived from the same underlying process, this approach guarantees that the explanations are always relevant to the predictions. We demonstrate the approach on a convolutional neural network for a UAV image classification task. We perform experiments using a forest trail image dataset and show empirically that the hybrid classifier can produce intuitive explanations without loss of predictive performance compared to the original neural network. We also show how the approach can be used to help identify potential issues in the network and training process.

Lee, Ritchie↗
NASA NTRS2019

Influence of Deep Convection on Cirrus and Water Vapor Concentration in the Upper Troposphere and Lower Stratosphere

It is well known that stratospheric humidity is primarily controlled by freeze drying (ice crystal growth and sedimentation) of air ascending across the cold tropical tropopause. However, the suggestion of an important source of water vapor from deep convection that extends above the tropical tropopause has persisted. There exists much anecdotal evidence of direct convective hydration of the lower stratosphere based on measurements from high altitude aircraft campaigns, but quantifying the impact of deep convection on the overall budget of stratospheric water vapor has proven challenging. The role of convection on the humidity of the upper troposphere and lower stratosphere (UTLS) is investigated in simulations of cirrus clouds along trajectories launched from given potential temperature level surfaces. The one-dimensional (vertical) cloud model tracks individual ice crystals through their life cycles, beginning with nucleation or detrainment from convection, followed by deposition growth, sedimentation and sublimation. Convective influence of the parcels is diagnosed by tracing the trajectories through time-dependent fields of convective cloud-top height adjusted to match the CloudSAT and CALIPSO statistics. Model simulations of UTLS water vapor and cloud fields are evaluated and constrained by comparison with MLS and CALIPSO measurements. The simulation results indicate that the overall impact of convection on water vapor near the tropical tropopause is 10-15%, while the impact on lower stratospheric humidity is no more than a few percent. Ice crystals detrained from deep convection have relatively small effect. The general implications for the importance of deep convection on UTLS humidity and cirrus cloud fraction will be discussed.

Ueyama, Rei↗
NASA NTRSDate not supplied

Monitoring Human Performance on Future Deep Space Missions Abstract

NASA and the commercial spacecraft community are working diligently to put the first woman on the moon in the 2024 timeframe. At the same time, NASA researchers are thinking about how to solve the even larger challenges that future deep space missions will bring. Space travel itself is difficult, but astronauts on deep space missions will face obstacles and unknowns never before experienced. In addition to the altered gravity and hostile/closed environment of a spacecraft, deep space crews will face increased radiation, isolation, and distance from Earth. During Extravehicular Activity (EVA, or “spacewalk”) operations, crew will experience increased physical and cognitive workload due to extended types, frequencies and durations of tasks performed on exploration missions in partial gravity environments. All of these stressors will impact crew physical and mental health and performance in difficult-to-anticipate ways. Crew autonomy may be one of the biggest challenges faced. Communication delays and blackouts will occur, and in those situations, the crew may not have access to the Mission Control Center (MCC). They may be forced to be solely dependent on each other and the available information onboard to stay alive, healthy, and achieve the mission. The only conceivable way to meet the challenges of Earth independence is to enable the crew to monitor their own health and performance -- preferably unobtrusively as they perform their duties. Technologies and techniques must be developed to aid the crew in these assessments. A deep space mission is expected to have relatively short periods of high cognitive demand, stress, and fatigue, alongside potentially long periods of cognitive underload during the transit, where boredom, loneliness, and depression can set in. Both ends of this spectrum are dangerous. Crew must be made aware when their task performance drops significantly, when their cognitive workload is too high, when they have lost situation awareness, or when they are too stressed or too fatigued to perform well. They must be able to identify these risks, and then mitigate them with countermeasures available onboard. A number of self-monitoring technologies are presently being explored by NASA to advance crew state determination capabilities. These range from real-time, physiological workload and situation awareness assessments, to crew health measurements determining physical and mental fitness for duty, to task performance metrics such as suit resource expenditures. For EVA tasks during surface exploration missions, biomedical information such as metabolic rate may be provided to crewmembers for situational awareness related to task performance efficiency. In addition, translation distances, hydration, nutrition, inspired CO2 exposure and other consumables usage rates may be useful input metrics for modeling individualized performance during tasks to inform crew or provide estimates of work efficiency. Oculomotor metrics such as gaze dwell time, pupilometry, and eye tracking collected in advanced helmet mounted displays could potentially be used to characterize crew situation awareness. This paper highlights some of these projects, and provides broader discussion about the need for advanced monitoring and smart technologies, as NASA takes the leap into the next generation of space exploration.

Kritina Holden↗
NASA NTRSDate not supplied

Jarosite Formation in Deep Antarctic Ice, an Earth Analogue to Unveil the Origin of Jarosite on Mars?

On Earth, jarosite is a weathering product forming in acidic-oxidative environments from the alteration of iron-bearing minerals in presence of liquid water. Typical settings where this iron-potassium hydrated sulphate is found, are weathering zones of pyrite-rich deposits, evaporative basins and fumaroles. Jarosite is not only known on Earth, it also occurs on Mars, where it has been identified by the Opportunity rover. The mineral was in fact recognized in the finely layered formations outcropping at Meridiani Planum and that were accurately investigated by the rover (Klingelhöfer et al. 2004). Since jarosite requires liquid water to form, its occurrence on Mars has been regarded as an evidence for the occurrence of liquid water in the geologic past of Mars (Elwood-Madden et al., 2004). Since then, many models have been proposed to describe the environments where the precipitation of Martian jarosite took place. The most accepted ones deal with evaporative basins similar to Earth’s playas, others concern volcanic activity and hydrothermal processes. An alternative proposal predicted that jarosite may have formed as a consequence of weathering of mineral dust trapped in massive ice deposits, i.e. the ice-weathering model (Niles & Michalsky, 2009). The hypothesis that jarosite formed on Mars because of low-temperature, acidic and water limited weathering, is not new (Burns, 1987), but until now no direct evidences were available to support it.A potential Earth analogue to investigate such processes is deep Antarctic ice. We present a first investigation of deep ice samples from the Talos Dome ice core (East Antarctica) aimed at the identification of englacial jarosite, so as to support the ice-weathering model. Evidences gathered through independent techniques showed that jarosite is actually present in deep Antarctic ice and results from the weathering of dust trapped into ice. The process is controlled by the re-crystallization of ice grains and the concurrent re-location of impurities at grain-junctions, which both depend on ice depth. This study demonstrates that the deep englacial environment is suitable for jarosite precipitation. Our findings support the hypothesis that, as originally predicted by the ice-weathering model, paleo ice-related processes have been important in thegeologic and geochemical history of Mars.

Lindsay P Keller↗
NASA NTRS1994

Small Deep Space Mission Telecommunications

Unique requirements imposed on deep space telecommunications, such as operation at extreme ranges, have historically led to high cost, one-of-a-kind spacecraft telecommunications systems. Yet future deep space misssions must fit within severe cost, mass and power constraints. JPL recently completed a study to find ways of reducing telecommunicaitons cost for future deep space missions. They identified and evaluated alternative telecommunicaitons systems architectures capable of satisfying these needs and design constraints. Future missions are expected to occur more frequently than in the past. The study recommends that a standard deep space transponder be developed. It also recommends spacecraft power amplifier and antenna development efforts.

telecommunications↗
NASA NTRS2017

SmallSat Navigation via the Deep Space Network: Lunar Transport

Spacecraft component miniaturization, the standardized CubeSat form factor, and a corresponding increase in launch ride-share availability have led to a renewed interest in smaller, more agile spacecraft missions. Naturally, interest in SmallSat capabilities extends outside of low Earth orbit for a variety of science and technology demonstration applications. As with larger missions, near-term deep-space SmallSats will more than likely rely on telecommunications and tracking via NASA's Deep Space Network or similar facilities. Given the predicted growth in the number of deep space missions, e ective use of telecommunication resources will be more critical than ever, even with Multiple Spacecraft Per Aperture capability. In particular, SmallSat missions will likely face stricter limitations on two-way contact with the tracking stations, thus making other options like one-way data types more attractive. While all missions must eventually develop their own detailed navigation plans, a common set of references is needed to support SmallSat missions, especially in the early development phases. Our investigation provides this initial survey of expected navigation performance for standard radiometric data types, from traditional two-way Doppler and ranging capabilities to one-way equivalents, including delta-di erential one-way range. In this investigation, we examine transport within the Earth-Moon region, the rst step outward from Earth into deep space exploration.

Wood, Lincoln↗